Segmen a ion-based lossless comp ession o bu n
wound images
Ca men Se ano
Begon
˜
a Acha Pin
˜
e o
A
´ ea de Teo ı
´adelaSen
˜
al y Comunicaciones
Escuela Supe io de Ingenie os
Uni e sidad de Se illa
Camino de los Descub imien os
s/n. 41092 Se illa, Spain
E-mail: [email p o ec ed], [email p o ec ed]
Ranga aj M. Rangayyan
Depa men o Elec ical and Compu e Enginee ing
Uni e si y o Calga y
Calga y Albe a, T2N 1N4, Canada
Lau a M. Roa
G upo de Ingenie ı
´a Biome
´dica
Escuela Supe io de Ingenie os
Uni e sidad de Se illa
Camino de los Descub imien os
s/n. 41092 Se illa Spain
Abs ac .
Colo images may be encoded by using a g ay-scale im-
age comp ession echnique on each o he h ee colo planes. Such
an app oach, howe e , does no ake ad an age o he co ela ion
exis ing be ween he colo planes. In his pape , a new
segmen a ion-based lossless comp ession me hod is p oposed o
colo images. The me hod exploi s he co ela ion exis ing among
he h ee colo planes by ea ing each pixel as a ec o o h ee
componen s, pe o ming egion g owing and di e ence ope a ions
using he ec o s, and applying a colo coo dina e ans o ma ion.
The me hod pe o med be e han he Join Pho og aphic Expe s
G oup (JPEG) s anda d by an a e age o 3.40 bi s/pixel wi h a da-
abase including ou na u al colo images o scene y, ou images o
bu n wounds, and ou ac al images, and i ou pe o med he Join
Bi-Le el Image expe s G oup (JBIG) s anda d by an a e age o
3.01 bi s/pixel. When applied o a da abase o 20 bu n wound im-
ages, he 24 bi s/pixel images we e e icien ly comp essed o 4.79
bi s/pixel, hen equi ing 4.16 bi s/pixel less han JPEG and 5.41
bi s/pixel less han JBIG.
© 2001 SPIE and IS&T.
[DOI: 10.1117/1.1383781]
1 In oduc ion
Lossless comp ession echniques a e essen ial in a chi al
and communica ion o medical images. Inc easing applica-
ions o elemedicine in he a eas o de ma ology and pa-
hology a e c ea ing new demands, such as ansmission
and a chi al o colo images. The Bu n Uni o he Hospi al
Uni e si a io Vi gen del Rocı
´o de Se illa and he Biomedi-
cal Enginee ing and Signal P ocessing G oups o he Uni-
e si y o Se illa a e de eloping a elemedicine p ojec
whe e he diagnosis o bu n pa ien s is pe o med wi h digi-
al colo pho og aphs. As au oma ic classi ica ion is pe -
o med in a p ocedu e whe e colo and ex u e a e essen ial,
a lossless comp ession me hod is needed o his pa icula
applica ion.
Al hough signi ican e o has been di ec ed owa ds he
de elopmen o lossless algo i hms o comp essing image
da a, mos o such me hods ha e been o ien ed owa ds
comp essing g ay-scale o wo- one 共bina y兲images. I is
commonly s a ed ha a ed-g een-blue 共RGB兲colo image
can be easily comp essed by using a g ay-scale image com-
p ession echnique on each o he h ee colo componen s.
Howe e , such an app oach does no ake ad an age o he
co ela ion exis ing be ween he colo planes.
Recen ly, a ew e o s ha e been di ec ed owa ds com-
p ession o ue-colo images by aking ad an age o hei
spec al co ela ion Singh e al.1p oposed an in ege -based
wa ele ans o m me hod, which was shown o be e icien
o comp ession o images wi h ine de ails. Memon and
Sayood2p oposed se e al me hods based on e o p edic-
ion models, and epo ed imp o emen o e he pe o -
mance o he Join Pho og aphic Expe s G oup 共JPEG兲
s anda d o abou 1.5 bi s pe colo pixel. Bocks ein3p o-
posed a new me hod based on a lossless ans o ma ion
om he RGB planes o o he planes, de ined as linea
combina ions o he o me , and comp essing each o he
new planes wi h a g ay-scale image lossless comp ession
algo i hm.4Van Assche e al.5p oposed a echnique based
on he Ka hunen–Loe
` e ans o m 共KLT兲 o deco ela e he
colo planes; comp ession a es o abou 0.5–2.0 bi s pe
pixel be e han hose p o ided by lossless JPEG we e ob-
Pape 99083 ecei ed Dec. 22, 1999; e ised manusc ip ecei ed Aug. 7, 2000;
accep ed o publica ion Feb. 23, 2001.
1017-9909/2001/$15.00 © 2001 SPIE and IS&T.
Jou nal o Elec onic Imaging 10(3), 720
–
726 (July 2001).
720 / Jou nal o Elec onic Imaging / July 2001 / Vol. 10(3)
Downloaded F om: h p://elec onicimaging.spiedigi allib a y.o g/ on 03/30/2017 Te ms o Use: h p://spiedigi allib a y.o g/ss/ e mso use.aspx
ained, bu wi h he disad an age o high compu a ional
ime.
In 1985, Kun e al.6p oposed a con ou - ex u e ap-
p oach o pic u e coding; hey called such app oaches
second-gene a ion image coding echniques, and hey ap-
plied i o lossy comp ession. The main idea behind his
echnique is o i s segmen he image in o nea ly homo-
geneous egions su ounded by con ou s such ha he con-
ou s co espond, as much as possible, o hose o he ob-
jec s in he image, and hen o encode he con ou and
ex u e in o ma ion sepa a ely. Because con ou s can be
ep esen ed as one-dimensional signals and pixels wi hin a
egion a e highly co ela ed, such me hods a e expec ed o
a ain high comp ession a ios. Al hough he idea seems o
be p omising, i s implemen a ion mee s a se ies o di icul-
ies. A majo p oblem exis s a i s e y impo an i s s ep
o segmen a ion, which de e mines he inal pe o mance o
he segmen a ion-based coding me hod. Mos o he seg-
men a ion algo i hms based upon his p inciple a e sophis-
ica ed and gi e good pe o mance only o speci ic ypes
o images.
Shen and Rangayyan7p oposed a segmen a ion-based
lossless image coding 共SLIC兲 echnique o adiog aphic
images. To o e come he p oblem men ioned abo e in e-
la ion o segmen a ion, hey p oposed a simple egion
g owing me hod. Ins ead o gene a ing a con ou se , a dis-
con inui y map is ob ained du ing he egion g owing p o-
cedu e. Concu en ly, he me hod also p o ides a co e-
sponding e o image based on he di e ence be ween each
pixel and i s co esponding ‘‘cen e pixel.’’ The las s ep in
he algo i hm is o code he discon inui y and e o da a
wi h he Join Bile el Image expe s G oup 共JBIG兲com-
p ession s anda d.8
We ha e ecen ly ex ended he SLIC algo i hm o colo
images.9In o de o exploi he co ela ion exis ing among
he h ee colo planes, ou algo i hm ea s each pixel o he
image as a h ee-dimensional 共3D兲 ec o 共RGB兲and pe -
o ms 3D egion g owing. The me hod p oduces a h ee-
componen e o image bu only a one-componen discon-
inui y map. Wi h a iew o ob ain be e comp ession, we
ha e included a lossless colo -coo dina e con e sion s ep
om RGB o he luminance, in-phase, and quad a u e-
phase 共YIQ兲 ep esen a ion sys em.10
We de o e Sec. 2 o p o ide de ails o he segmen a ion-
based lossless colo image coding 共SLCIC兲algo i hm, and
p o ide he esul s o i s compa ison wi h he JPEG in e -
na ional s anda d o lossless s ill-image comp ession11 in
Sec. 3.
2 Segmen a ion-Based Lossless Coding
Algo i hm o Colo Images
In lossless image comp ession, he ask is usually spli in o
wo s ages: one is image ans o ma ion, wi h he pu pose
o da a deco ela ion; he o he is encoding o he ans-
o med da a. In he SLCIC algo i hm, image ans o ma ion
is achie ed in bo h he egion g owing p ocedu e and, la e ,
in he JBIG algo i hm. The JBIG algo i hm uses an adap-
i e h ee-dimensional coding model ollowed by an adap-
i e a i hme ic code .8Figu e 1 gi es a block diag am dem-
ons a ing he a ious s eps in he SLCIC p ocedu e.
2.1
Region G owing Algo i hm
As desc ibed by Shen and Rangayyan7 o single-
componen images, he egion g owing p ocedu e s a s
wi h a single pixel, called he seed pixel. Each o he seed’s
ou -connec ed neighbo pixels, scanned in a ixed o de , is
checked wi h a egion g owing 共o inclusion兲condi ion. I
he condi ion is sa is ied, he neighbo pixel is included in
he egion. The p ocedu e is ecu si ely con inued un il no
spa ially connec ed pixel mee s he g owing condi ion. A
new egion g owing p ocedu e is hen s a ed wi h he nex
pixel o he image which is no al eady a membe o a
egion. The p ocedu e ends when e e y pixel in he image
has been included in one o he egions g own.
The egion g owing condi ions used in his wo k a e 共i兲
he neighbo pixel is no a membe o any o he egions
al eady g own, and 共ii兲 he absolu e di e ence be ween he
Fig. 1 Summa y o he SLCIC p ocedu e.
Segmen a ion-based lossless comp ession...
Jou nal o Elec onic Imaging / July 2001 / Vol. 10(3) / 721
Downloaded F om: h p://elec onicimaging.spiedigi allib a y.o g/ on 03/30/2017 Te ms o Use: h p://spiedigi allib a y.o g/ss/ e mso use.aspx
ed, g een, and blue in ensi ies o he neighbo pixel and
hose o he co esponding ‘‘cen e pixel’’ is less han a
p ede ined e o –le el. The cen e pixel is de ined as ha
pixel which is being used as he e e ence o check i s ou -
connec ed neighbo s o inclusion in he egion being
g own; he cen e pixel would ha e al eady been included
in he egion. When a new neighbo pixel is included in he
egion being g own, i s e o –le el-shi -up di e ence wi h
espec o i s cen e pixel is s o ed as he pixel’s ‘‘e o ’’
alue; his alue is a ec o o h ee componen s. I only he
i s o he wo egion g owing condi ions is me , he dis-
con inui y index o he pixel is inc emen ed. The discon i-
nui y index indica es how many imes a pixel has been
es ed o be included in a egion and inally i has no been
included. The e o e, a e egion g owing, a ‘‘discon inui y
index image da a pa ’’ and a h ee-componen ‘‘e o im-
age da a pa ’’ will be ob ained. The maximum alue o he
discon inui y index is ou . Mos o he p e iously epo ed
segmen a ion-based coding algo i hms include con ou cod-
ing and egion coding; ins ead o hese s eps, we use a
discon inui y index da a pa and an e o image da a pa .
The e o –le el is de e mined by he p eselec ed
e o –bi s assigned o each o he h ee componen s o he
ec o as e o –le el⫽2e o –bi s⫺1. Fo ins ance, i he
e o image is allowed o ake up o 5 b/colo -plane-pixel
o each componen (e o –bi s⫽5), he co esponding
e o –le el is 16; in o he wo ds, he allowed di e ence
ange is hen 关⫺15, 15兴. The e o alue o he seed pixel o
each egion is de ined as he ec o o med by he low
e o –bi s bi s o each componen . The alue o he high
(N⫺e o –bi s) bi s o he h ee componen s o he pixel
is s o ed in a ‘‘high-bi s seed da a pa ,’’ whe e Nis he
numbe o b/pixel in he o iginal image da a.
The abo e h ee da a pa s a e used o ully eco e he
o iginal image du ing he decoding p ocess. The egion
g owing condi ions du ing decoding a e 共i兲 he neighbo
pixel unde conside a ion o inclusion is no in any o he
p e iously g own egions, and 共ii兲 he discon inui y index
o he pixel is equal o ze o. When he condi ions a e me
o a pixel, i s pixel alue is es o ed as he sum o i s
e o –le el-shi -down e o alue and i s cen e pixel
alue 共excep o he seed pixel o e e y egion, o which
he la e is gi en by he high-bi s seed da a pa 兲. I only
he i s o he wo condi ions is sa is ied, he discon inui y
index o he pixel is dec emen ed. Thus he discon inui y
index gene a ed du ing segmen a ion is used o guide e-
gion g owing du ing decoding.
The egion g owing p ocedu e may be iewed as adap-
i e scanning o he image wi h he aim o main aining a
localized di e ence o e o alue wi hin a limi ed dynamic
ange p especi ied and con olled by e o –bi s.
Figu e 2 is a simple example o illus a ion o he e-
gion g owing p ocedu e and i s esul . The o iginal image is
he 512⫻512 24-bi Lena image. A 5⫻5 segmen o he
image is shown in Fig. 2共a兲. The alue o e o bi s is se o
h ee in his example. Figu e 2共b兲is he esul o egion
g owing. The co esponding h ee da a pa s, namely dis-
con inui y index image da a, e o image da a, and high-bi s
seed da a, a e shown in Figs. 2共c兲–2共e兲.
2.2
Segmen a ion-Based Lossless Colo Image
Comp ession P ocedu e
The comple e SLCIC p ocedu e is illus a ed in Fig. 1. A
he encoding end, he o iginal image is ans o med by he
egion g owing p ocedu e in o h ee pa s: he discon inui y
index image da a pa wi h one-dimensional elemen s, and
he e o image da a pa and he high-bi s seed da a pa
composed o 3D ec o s. The i s wo da a pa s a e hen
g ay coded, b oken down in o bi planes, and inally JBIG
coded. The las da a pa is s o ed o ansmi ed as-is; i
needs (N⫺e o –bi s)*3 bi s pe seed pixel.
A he ecei ing end JBIG-coded da a iles a e JBIG-
decoded i s and hen he g ay-coded bi planes a e com-
posed back o bina y code. Finally, he pa s a e combined
oge he by he same egion g owing p ocedu e o eco e
as in he encoding scheme o eco e he o iginal image.
2.3
Lossless RGB- o-YIQ T ans o ma ion
Usually, when coding colo images wi h loss, a ans o ma-
ion om RGB colo coo dina es o YIQ is pe o med. This
is based upon he obse a ion ha he Y componen is un-
co ela ed wi h he ch ominance componen s 共I and Q兲, and
ha mos high- equency componen s o a colo image a e
concen a ed in he Y componen .12 In lossless comp es-
sion, he second ad an age canno be exploi ed, bu he i s
one is used o gain imp o ed comp ession.
To change he colo coo dina es om RGB o YIQ he
ollowing linea ans o ma ion is pe o med12:
Fig. 2 Simple example o he egion g owing p ocedu e and i s e-
sul wi h
e o bi s
se obe h ee:(a)a5⫻5 segmen o he 512
⫻512 24-bi colo Lena image, whe e each alue ep esen s he R,
G, and B componen , espec i ely; (b) esul o egion g owing; (c)
co esponding discon inui y index da a pa ; (d) co esponding e o
image da a pa ; (e) he co esponding high-bi s seed da a pa .
Se ano e al.
722 / Jou nal o Elec onic Imaging / July 2001 / Vol. 10(3)
Downloaded F om: h p://elec onicimaging.spiedigi allib a y.o g/ on 03/30/2017 Te ms o Use: h p://spiedigi allib a y.o g/ss/ e mso use.aspx
冋
Y
I
Q
册
⫽
冋
0.299 0.587 0.114
0.596 ⫺0.274 ⫺0.322
0.211 ⫺0.523 0.312
册
冋
R
G
B
册
.共1兲
Howe e , his ans o ma ion canno be applied in loss-
less comp ession because i in ol es loa ing-poin ope a-
ions, hus equi ing quan iza ion. In o de o a oid quan i-
za ion e o , a ans o ma ion based on in ege a i hme ic is
equi ed. Such a ans o ma ion is comple ely e e sible
and hence lossless, and is gi en by:1
Yl⫽
b
b
R⫹B
2
c
⫹G
2
c
,共2兲
Il⫽R⫺B, 共3兲
Ql⫽
b
R⫹B
2
c
⫺G, 共4兲
whe e b•cdeno es he loo unc ion.
The in e se ans o ma ion is gi en by:
R⫽Yl⫹
b
Ql⫹1
2
c
⫹
b
Il⫹1
2
c
,共5兲
G⫽Yl⫺
b
Ql
2
c
,共6兲
B⫽Yl⫹
b
Ql⫹1
2
c
⫺
b
Il
2
c
.共7兲
The subsc ip lis used o indica e he lossless na u e o
he ans o ma ion. This ans o ma ion pe o ms he YIQ
one, bu wi hou losses, and i is p o ed in Re . 1. I is
impo an o no e ha in o de o p ese e he lossless na-
u e o he algo i hm, one bi mus be added o each o he
ch ominance e o componen s 共one o I and one o Q兲
due o he sign ha appea s when con e ing om RGB o
YlIlQl.
3 Expe imen al Resul s
The SLCIC echnique was es ed using 12 24-bi colo im-
ages o di e en sizes and na u e. The pe o mance o he
SLCIC echnique was compa ed wi h ha o he lossless
JPEG 7 s anda d and he JBIG s anda d. The ini ial es
image se includes ou images o scene y 共Lena, Peppe s,
Pa o s, and Ge many兲, ou images o bu n wounds, and
ou ac al images 共 om h p://di .yahoo.com/A s/
Visual–A s/Compu e –Gene a ed/F ac als/A is s/兲. The
bu n wound images ha e been aken ollowing a p o ocol
explained in Re . 13. In his p o ocol a digi al pho og aph
came a is used, and he pho og aphs a e s o ed as ue-colo
ones, i.e., 24 bi s pe pixel, 8 bi s pe each colo componen
共RGB: ed, g een, blue兲.
Figu es 3–5 show he e o and he discon inui y index
da a pa s as images o h ee o he es images used. I can
be obse ed in all o he cases illus a ed ha he e o
image does no con ain any signi ican ch oma ici y in o -
ma ion 共ac ually hey look like g ay-scale images being
colo ones兲, bu e ains a po ion o he bounda y in o ma-
ion o he image. The discon inui y index clea ly co e-
sponds o edges in he image.
The comp ession pe o mance o he SLCIC me hod
wi h he ini ial se o 12 images is summa ized in Tables 1
and 2 along wi h he esul s o JPEG and JBIG comp es-
sion. The SLCIC me hod has a unable pa ame e , which is
e o –bi s. The SLCIC me hod has ou pe o med lossless
JPEG on he a e age o he es image se used by 0.68 bi s
pe colo pixel 共wi h he o iginal images ha ing 24 b/pixel
in he RGB domain兲, and JBIG by 0.29 b/pixel. As shown
in Table 1, when using he YlIlQlcoo dina es, he pe o -
mance o he SLCIC is much be e , p o iding an a e age
o 9.24 b/pixel. The me hod ou pe o med s anda d JPEG
by an a e age o 3.34 b/pixel, JBIG by 2.95 b/pixel, and
SLCIC wi h RGB coo dina es by 2.66 b/pixel. In Table 2 a
compa ison o he code and decode imes o SLCIC,
JPEG, and JBIG is done, whe e he imes o eading and
w i ing he images o and om he disk a e also conside ed
and, o he case o he SLCIC algo i hm, he ime em-
ployed in he con e sion om RGB o YIQ is also in-
cluded. Al hough in e nally SLCIC uses JBIG, i ge s as e
imes han JBIG alone. This is due o he ac ha JBIG
ac ing alone has o code 24 bi planes whe eas JBIG join o
SLCIC only has o code he numbe o bi planes de e -
mined by he pa ame e e o –bi s. Addi ionally, he egion
g owing p ocedu e does no add a signi ican quan i y o
he o al compu a ional ime. The JBIG so wa e we ha e
Table 1 Compa ison o he pe o mances o SLCIC, JBIG, and
JPEG using wel e 24 b images by b/pixel.
Image JPEG
(b/pixel) JBIG
(b/pixel)
SLCIC (b/pix)
RGB Y
l
I
l
Q
l
Scene y:
1. Peppe s 15.69 15.65 15.99 16.29
2. Ge many 17.73 17.49 16.49 12.35
3. Lena 14.79 15.12 15.08 14.98
4. Pa o s 18.04 12.06 18.01 9.63
A e age o scene y: 16.56 15.08 16.39 13.31
Bu n wounds:
1. Pho o 1 10.8 12.43 10.64 5.87
2. Pho o 2 7.36 8.19 6.56 4.04
3. Pho o 3 7.45 8.68 6.8 4.32
4. Pho o 4 7.33 8.67 6.74 4.22
A e age o bu n wounds: 8.24 9.49 7.69 4.61
F ac als:
1. A lan is 15.12 14.05 13.76 12.76
2. 7 hm 12.09 11.27 11.00 10.97
3. Mandsil 14.58 14.46 13.45 7.90
4. Yinyw hm 9.95 8.17 8.25 7.62
A e age o ac als: 12.94 11.99 11.62 9.81
A e age o all images: 12.58 12.19 11.9 9.24
Segmen a ion-based lossless comp ession...
Jou nal o Elec onic Imaging / July 2001 / Vol. 10(3) / 723
Downloaded F om: h p://elec onicimaging.spiedigi allib a y.o g/ on 03/30/2017 Te ms o Use: h p://spiedigi allib a y.o g/ss/ e mso use.aspx
Fig. 3 Lena: (a) o iginal image; (b) e o image; (c) discon inui y index image.
Fig. 4 Bu n wound: (a) o iginal image; (b) e o image; (c) discon inui y index image.
Fig. 5 F ac al: (a) o iginal image; (b) e o image; (c) discon inui y index image.
Se ano e al.
724 / Jou nal o Elec onic Imaging / July 2001 / Vol. 10(3)
Downloaded F om: h p://elec onicimaging.spiedigi allib a y.o g/ on 03/30/2017 Te ms o Use: h p://spiedigi allib a y.o g/ss/ e mso use.aspx

employed is a ee dis ibu ion e sion de eloped by AT&T
in 1991.
A e examining he Y, I, and Q componen images
sepa a ely, we ealized ha he I and Q componen s we e
much mo e uni o m han he luminance one so, hey would
need less e o –bi s o be encoded han he Y componen .
We changed he algo i hm in o de o code each componen
wi h di e en numbe o e o –bi s, and we go be e e-
sul s, ha a e summa ized in Table 3. To a oid con usions
we ha e called his modi ica ion o he SLCIC algo i hm,
SLCIC2. Wi h he SLCIC2 he imp o emen gained o e
JPEG is 3.40 b/pixel on a e age and 3.01 b/pixel o e
JBIG.
Due o he good esul s ob ained wi h bu n wound im-
ages, we we e encou aged o s udy he algo i hm o ou
pa icula applica ion. Hence, we es ed he SLCIC p oce-
du e wi h a la ge da abase o 20 bu n wound images. The
esul s a e summa ized in Table 4, gi en as he mean and
he a iance o SLCIC, SLCIC2, JPEG, and JBIG, whe e
we can see ha he SLCIC me hod has ou pe o med s an-
da d JPEG by an a e age o 4.13 b/pixel and JBIG by 5.38
b/pixel, and he SLCIC2 has ou pe o med JPEG by an
a e age o 4.16 b/pixel and JBIG by 5.41 b/pixel. The ea-
son o such a good pe o mance wi h bu n wound images
can be ound in he special ea u es o he images: hey
ha e uni o m colo s, such ha majo i y o i s in o ma ion is
loca ed in he luminance componen exclusi ely. Addi ion-
ally, e en in he luminance componen , he e a e la ge,
almos -uni o m egions.
In he same way as he e o ma ix and he discon inui y
index ma ix a e coded wi h JBIG a e he egion g owing
s ep, we expe imen ed wi h encoding he seed ec o wi h
JBIG. Howe e , he esul s we e poo because he numbe
o egions ob ained was no la ge.
4 Discussion
While he e ha e been some wo ks on lossless comp ession
o colo images, e y ew ha e exploi ed he no ion o wha
has been called second-gene a ion image coding,14 in pa -
icula he segmen a ion-based app oach. In his a icle, a
me hod based on segmen a ion 共 egion g owing兲has been
p esen ed. When es ed wi h se e al gene al-pu pose im-
ages, he p oposed me hod esul ed in an imp o emen o
3.40 bi s pe colo pixel o e he lossless JPEG s anda d
and o 3.01 bi s pe colo pixel o e he JBIG s anda d.
When es ed wi h a da abase o 20 bu n wound images, he
me hod ou pe o med s anda d JPEG by 4.16 bi s pe colo
pixel, and s anda d JBIG by 5.41 bi s pe colo pixel. As we
said, he eason o such a good pe o mance wi h bu n
wound images can be ound in he special ea u es o he
images: hey ha e uni o m colo s, such ha majo i y o i s
in o ma ion is loca ed in he luminance componen exclu-
si ely. Addi ionally, e en in he luminance componen ,
he e a e la ge, almos -uni o m egions. So, we ge e y
good esul s when conside ing di e en numbe o
e o –bi s o each componen . The ch ominance compo-
nen s 共I and Q兲need less e o –bi s han he luminance
one, because hey ca y less in o ma ion.
The compu a ional speed o SLCIC is no e y slow
compa ing wi h ha o JPEG due o he use o an e icien
Table 2 Compa ison o code and decode ime o JPEG, JBIG, and
SLCIC-Y
l
I
l
Q
l
. Compu ing ime o less han1sisen e edas0in he
able.
Image Size
(col⫻ ow⫻b/pixel)
Code/decode
ime (s)
JPEG JBIG SLCIC
Scene y:
1. Peppe s 512⫻512⫻24 2/0 14/14 12/12
2. Ge many 768⫻512⫻24 2/0 19/19 18/18
3. Lena 512⫻512⫻24 2/0 13/13 12/12
4. Pa o s 768⫻512⫻24 3/0 19/19 16/16
Bu n wounds:
1. Pho o 1 832⫻624⫻24 4/1 23/23 17/17
2. Pho o 2 832⫻624⫻24 4/1 22/22 19/19
3. Pho o 3 832⫻624⫻24 5/1 22/22 17/17
4. Pho o 4 832⫻624⫻24 5/1 21/21 18/18
F ac als:
1. A lan is 320⫻240⫻24 0/0 4/4 1/1
2.7 hm 160⫻120⫻24 0/0 1/1 0/0
3. Mandsil 160⫻159⫻24 0/0 1/1 0/0
4. Yinyw hm 320⫻240⫻24 0/0 4/4 1/1
Table 3 Compa ison o he pe o mances o SLCIC2, JBIG, and
JPEG using wel e 24 b images by b/pixel. The SLCIC2 algo i hm is
implemen ed using di e en numbe o e o –bi s o he Y, I, and Q
componen s.
Image JPEG
(b/pixel) JBIG
(b/pixel) SLCIC2
(b/pix)
Scene y:
1. Peppe s 15.69 15.65 16.29
2. Ge many 17.73 17.49 12.32
3. Lena 14.79 15.12 14.97
4. Pa o s 18.04 12.06 9.61
A e age o scene y: 16.56 15.08 13.30
Bu n wounds:
1. Pho o 1 10.8 12.43 5.83
2. Pho o 2 7.36 8.19 4.01
3. Pho o 3 7.45 8.68 4.29
4. Pho o 4 7.33 8.67 4.20
A e age o bu n wounds: 8.24 9.49 4.58
F ac als:
1. A lan is 15.12 14.05 12.69
2. 7 hm 12.09 11.27 10.80
3. Mandsil 14.58 14.46 7.58
4. Yinyw hm 9.95 8.17 7.55
A e age o ac als: 12.94 11.99 9.66
A e age o all images: 12.58 12.19 9.18
Segmen a ion-based lossless comp ession...
Jou nal o Elec onic Imaging / July 2001 / Vol. 10(3) / 725
Downloaded F om: h p://elec onicimaging.spiedigi allib a y.o g/ on 03/30/2017 Te ms o Use: h p://spiedigi allib a y.o g/ss/ e mso use.aspx
egion g owing me hod. Mos o he compu a ional cos o
SLCIC is due o JBIG coding included in he algo i hm.
The egion g owing p ocedu e does no add a signi ican
quan i y o he o al compu a ional ime. In a SUN Ul a
SPARC 共120 MB memo y, 2.1 GB disk, clock 167 MHz,
112 KB cache memo y兲SLCIC equi ed 1–20 s o encode/
decode he images used; JPEG equi ed 1–5 s o he same
images.
We a e explo ing possibili ies o u he imp o emen in
he pe o mance o SLCIC by analyzing he na u e o he
e o image. One imp o emen unde conside a ion is, in-
s ead o changing colo coo dina es o he whole image, o
change he ep esen a ion o only he e o image om he
RGB planes o hue, sa u a ion, and alue 共HSV兲o o
YlIlQl. We a e also explo ing he possibili y o using ech-
niques o he han JBIG, a e he egion g owing s ep, o
code he e o and discon inui y pa s in o de o ake in o
accoun he indi idual cha ac e is ics o each pa .
Acknowledgmen s
This wo k was suppo ed by g an s om CICYT 共TIC-96-
0500-C10-08兲and Jun a de Andalucı
´a o Spain and he
Na u al Sciences and Enginee ing Resea ch Council
共NSERC兲o Canada. We hank Liang Shen o help wi h
he segmen a ion-based lossless image coding echnique o
monoch ome images, and Mihai Ciuc o assis ance wi h
colo image p ocessing. We also hank D . Toma
´sGo
´mez-
Cı
´a o he Unidad de Quemados o he Hospi al Uni e si-
a io Vi gen del Rocı
´o de Se illa o p o iding he bu n
wound images.
Re e ences
1. I. Singh, P. Aga hoklis, and A. An oniou, ‘‘Lossless comp ession o
colo images using an imp o ed in ege -based nonlinea wa ele
ans o m,’’ P oc. IEEE In . Symp. Ci cui s Sys ., 2609–2612 共1997兲.
2. N. D. Memon and K. Sayood, ‘‘Lossless comp ession o RGB colo
images,’’ Op . Eng. 34共6兲, 1711–1717 共1995兲.
3. I. M. Bocks ein, ‘‘An adap i e me hod o lossless comp ession o
colo images,’’ P oc. SPIE. Image P oc. Compu . Op ., 2363, 300–
306 共1994兲.
4. I. M. Bocks ein, ‘‘A me hod o lossless image comp ession,’’ in Pa -
e n Recogni ion and Image Analysis, W. Poelzlei ne and E. Wenge ,
Eds., pp. 92–98, Sch i en eihe de Oes e eichischen Compu e Ge-
sellscha , Wien, Aus ia 共1993兲.
5. S. Van Assche, W. Philips, and I. Lemahieu, ‘‘Lossless comp ession
o p e-p ess images using linea colo deco ela ion,’’ P oc. IEEE
Da a Comp ession Con ., 578 共1998兲.
6. M. Kun , A. Ikonomopoulos, and M. Koche , ‘‘Second-gene a ion
image-coding echniques,’’ P oc. IEEE 73共4兲, 549–574 共1985兲.
7. L. Shen, and R. M. Rangayyan, ‘‘A segmen a ion-based lossless im-
age coding me hod o high- esolu ion medical image comp ession,’’
IEEE T ans. Med. Imaging 16共3兲, 301–307 共1997兲.
8. ‘‘P og essi e bi-le el image comp ession,’’ In e na ional Teleg aph
and Telephone Consul a i e Commi ee 共CCITT兲. Recommenda ion
T. 82, 1993.
9. B. Acha, C. Se ano, R. M. Rangayyan, and L. M. Roa, ‘‘Lossless
comp ession algo i hm o colou images,’’ Elec on. Le . 35共3兲,
214–215 共1999兲.
10. C. Se ano, B. Acha, and R. M. Rangayyan, ‘‘Segmen a ion-based
lossless comp ession o colo images,’’ in P oc. Ten h In e na ional
Con . on Image Analysis and P ocessing (ICIAP’99), Venice, I aly,
pp. 90–94 共1999兲.
11. G. K. Wallace, ‘‘The JPEG s ill pic u e comp ession s anda d,’’ Com-
mun. ACM 34共4兲, 30–44 共1991兲.
12. C. S. Lim, Two-dimensional Signal and Image P ocessing, P en ice
Hall Signal P ocessing Se ies, P en ice-Hall, Englewood Cli s, NJ,
共1990兲, pp. 422–423.
13. C. Se ano, L. Roa, and B. Acha, ‘‘E alua ion o a elemedicine pla -
o m in a bu n uni ,’’ P oc. o IEEE In e na ional Con . on In o ma-
ion Technology Applica ions in Biomedicine, Washing on DC, pp.
121–126 共1998兲.
14. S. Van Assche, W. Philips, and I. Lemahieu, ‘‘Lossless comp ession
o p e-p ess images using a no el colo deco ela ion echnique,’’
P oc. SPIE 3308, 85–92 共1998兲.
Ca men Se ano ecei ed he MS in Tele-
communica ion Enginee ing om he Uni-
e si y o Se ille, Spain, in 1996. In 1996,
she joined he Signal P ocessing and Com-
munica ion G oup a he same uni e si y,
whe e she is cu en ly an associa e p o es-
so . He esea ch in e es s conce n image
p ocessing and, in pa icula , colo image
segmen a ion and comp ession, mainly
wi h biomedical applica ions.
Begon
˜a Acha Pin
˜e o s udied Telecommu-
nica ion Enginee ing a Enginee ing Fac-
ul y o he Uni e si y o Se ille om 1991 o
1996. She has been wo king as an associ-
a e p o esso since 1996 in he Signal P o-
cessing and Communica ions G oup o he
Elec onic Enginee ing Depa men o he
Uni e si y o Se ille. She is cu en ly wo k-
ing owa d he PhD. He cu en esea ch
ac i i ies include wo ks in he ield o image
p ocessing and i s medical applica ions.
Ranga aj M. Rangayyan ecei ed his
Bachelo o Enginee ing deg ee in Elec-
onics and Communica ion in 1976 om
he Uni e si y o Myso e a he P.E.S. Col-
lege o Enginee ing, Mandya, Ka na aka,
India, and his PhD in Elec ical Enginee ing
om he Indian Ins i u e o Science, Banga-
lo e, Ka na aka, India, in 1980. He was
wi h he Uni e si y o Mani oba, Winnipeg,
Mani oba, Canada, om 1981 o 1984. He
is a p esen a P o esso wi h he Depa -
men o Elec ical and Compu e Enginee ing (and an Adjunc P o-
esso o Su ge y and Radiology) a he Uni e si y o Calga y, Cal-
ga y, Albe a, Canada. His esea ch in e es s a e in he a eas o
digi al signal and image p ocessing, biomedical signal analysis,
medical imaging and image analysis, and compu e ision. His cu -
en esea ch p ojec s a e on mammog aphic image enhancemen
and analysis o compu e -aided diagnosis o b eas cance ; egion-
based image p ocessing; knee-join ib a ion signal analysis o
nonin asi e diagnosis o a icula ca ilage pa hology; and analysis
o ex u ed images by ceps al il e ing and soni ica ion. He is he
winne o he 1997 Resea ch Excellence Awa d o he Depa men
o Elec ical and Compu e Enginee ing, and he 1997 Resea ch
Awa d o he Facul y o Enginee ing, Uni e si y o Calga y. He was
ecognized by he IEEE wi h he awa d o he Thi d Millennium
Medal in 2000, and elec ed as a Fellow o he IEEE in 2001.
Lau a M. Roa: Biog aphy and pho og aph no a ailable.
Table 4 Compa ison o he pe o mances o SLCIC, SLCIC2,
JPEG, and JBIG by b/pixel using 20 bu n wound images. Each im-
age is o size 832⫻624 pixels, wi h 24 b/pixel in he RGB ep esen-
a ion.
20 bu n wound
images JPEG
(b/pixel) JBIG
(b/pixel) SLCIC
(b/pixel) SLCIC2
(b/pixel)
A e age 8.95 10.20 4.82 4.79
Va iance 2.16 2.07 0.54 0.54
Se ano e al.
726 / Jou nal o Elec onic Imaging / July 2001 / Vol. 10(3)
Downloaded F om: h p://elec onicimaging.spiedigi allib a y.o g/ on 03/30/2017 Te ms o Use: h p://spiedigi allib a y.o g/ss/ e mso use.aspx